SOTAVerified

Question Answering

Question answering can be segmented into domain-specific tasks like community question answering and knowledge-base question answering. Popular benchmark datasets for evaluation question answering systems include SQuAD, HotPotQA, bAbI, TriviaQA, WikiQA, and many others. Models for question answering are typically evaluated on metrics like EM and F1. Some recent top performing models are T5 and XLNet.

( Image credit: SQuAD )

Papers

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Showing 2176–2200 of 10817 papers

TitleStatusHype
Reasoning with Large Language Models, a Survey—0
TM-PATHVQA:90000+ Textless Multilingual Questions for Medical Visual Question Answering—0
Evaluating Large Language Models with fmevalCode3
Evaluation of RAG Metrics for Question Answering in the Telecom Domain—0
MixGR: Enhancing Retriever Generalization for Scientific Domain through Complementary GranularityCode1
Unraveling the Truth: Do VLMs really Understand Charts? A Deep Dive into Consistency and Robustness—0
FabGPT: An Efficient Large Multimodal Model for Complex Wafer Defect Knowledge Queries—0
Graphusion: Leveraging Large Language Models for Scientific Knowledge Graph Fusion and Construction in NLP EducationCode1
Benchmarking Vision Language Models for Cultural Understanding—0
BiasAlert: A Plug-and-play Tool for Social Bias Detection in LLMs—0
GenSco: Can Question Decomposition based Passage Alignment improve Question Answering?—0
Lost and Found: Overcoming Detector Failures in Online Multi-Object TrackingCode1
sPhinX: Sample Efficient Multilingual Instruction Fine-Tuning Through N-shot Guided Prompting—0
IoT-LM: Large Multisensory Language Models for the Internet of ThingsCode1
NativQA: Multilingual Culturally-Aligned Natural Query for LLMs—0
Bridging the Gap Between Information Seeking and Product Search Systems: Q&A Recommendation for E-commerce—0
GOFA: A Generative One-For-All Model for Joint Graph Language ModelingCode2
PersonaRAG: Enhancing Retrieval-Augmented Generation Systems with User-Centric AgentsCode2
One Stone, Four Birds: A Comprehensive Solution for QA System Using Supervised Contrastive LearningCode0
A Mathematical Framework, a Taxonomy of Modeling Paradigms, and a Suite of Learning Techniques for Neural-Symbolic SystemsCode0
CompAct: Compressing Retrieved Documents Actively for Question AnsweringCode1
DAHRS: Divergence-Aware Hallucination-Remediated SRL Projection—0
TelecomGPT: A Framework to Build Telecom-Specfic Large Language Models—0
SPIQA: A Dataset for Multimodal Question Answering on Scientific PapersCode2
Model Surgery: Modulating LLM's Behavior Via Simple Parameter EditingCode1
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All datasetsSQuAD2.0SQuAD1.1HotpotQAPIQABoolQCOPATriviaQASQuAD1.1 devNatural QuestionsOpenBookQATruthfulQAMultiRC

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1IE-Net (ensemble)EM90.94—Unverified
2FPNet (ensemble)EM90.87—Unverified
3IE-NetV2 (ensemble)EM90.86—Unverified
4SA-Net on Albert (ensemble)EM90.72—Unverified
5SA-Net-V2 (ensemble)EM90.68—Unverified
6FPNet (ensemble)EM90.6—Unverified
7Retro-Reader (ensemble)EM90.58—Unverified
8EntitySpanFocusV2 (ensemble)EM90.52—Unverified
9TransNets + SFVerifier + SFEnsembler (ensemble)EM90.49—Unverified
10EntitySpanFocus+AT (ensemble)EM90.45—Unverified